// This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// Copyright (C) 2011-2014 Gael Guennebaud <gael.guennebaud@inria.fr>
// Copyright (C) 2010 Daniel Lowengrub <lowdanie@gmail.com>
//
// This Source Code Form is subject to the terms of the Mozilla
// Public License v. 2.0. If a copy of the MPL was not distributed
// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.

#ifndef EIGEN_SPARSEVIEW_H
#define EIGEN_SPARSEVIEW_H

namespace Eigen {

namespace internal {

    template <typename MatrixType> struct traits<SparseView<MatrixType>> : traits<MatrixType>
    {
        typedef typename MatrixType::StorageIndex StorageIndex;
        typedef Sparse StorageKind;
        enum
        {
            Flags = int(traits<MatrixType>::Flags) & (RowMajorBit)
        };
    };

}  // end namespace internal

/** \ingroup SparseCore_Module
  * \class SparseView
  *
  * \brief Expression of a dense or sparse matrix with zero or too small values removed
  *
  * \tparam MatrixType the type of the object of which we are removing the small entries
  *
  * This class represents an expression of a given dense or sparse matrix with
  * entries smaller than \c reference * \c epsilon are removed.
  * It is the return type of MatrixBase::sparseView() and SparseMatrixBase::pruned()
  * and most of the time this is the only way it is used.
  *
  * \sa MatrixBase::sparseView(), SparseMatrixBase::pruned()
  */
template <typename MatrixType> class SparseView : public SparseMatrixBase<SparseView<MatrixType>>
{
    typedef typename MatrixType::Nested MatrixTypeNested;
    typedef typename internal::remove_all<MatrixTypeNested>::type _MatrixTypeNested;
    typedef SparseMatrixBase<SparseView> Base;

public:
    EIGEN_SPARSE_PUBLIC_INTERFACE(SparseView)
    typedef typename internal::remove_all<MatrixType>::type NestedExpression;

    explicit SparseView(const MatrixType& mat, const Scalar& reference = Scalar(0), const RealScalar& epsilon = NumTraits<Scalar>::dummy_precision())
        : m_matrix(mat), m_reference(reference), m_epsilon(epsilon)
    {
    }

    inline Index rows() const { return m_matrix.rows(); }
    inline Index cols() const { return m_matrix.cols(); }

    inline Index innerSize() const { return m_matrix.innerSize(); }
    inline Index outerSize() const { return m_matrix.outerSize(); }

    /** \returns the nested expression */
    const typename internal::remove_all<MatrixTypeNested>::type& nestedExpression() const { return m_matrix; }

    Scalar reference() const { return m_reference; }
    RealScalar epsilon() const { return m_epsilon; }

protected:
    MatrixTypeNested m_matrix;
    Scalar m_reference;
    RealScalar m_epsilon;
};

namespace internal {

    // TODO find a way to unify the two following variants
    // This is tricky because implementing an inner iterator on top of an IndexBased evaluator is
    // not easy because the evaluators do not expose the sizes of the underlying expression.

    template <typename ArgType> struct unary_evaluator<SparseView<ArgType>, IteratorBased> : public evaluator_base<SparseView<ArgType>>
    {
        typedef typename evaluator<ArgType>::InnerIterator EvalIterator;

    public:
        typedef SparseView<ArgType> XprType;

        class InnerIterator : public EvalIterator
        {
        protected:
            typedef typename XprType::Scalar Scalar;

        public:
            EIGEN_STRONG_INLINE InnerIterator(const unary_evaluator& sve, Index outer) : EvalIterator(sve.m_argImpl, outer), m_view(sve.m_view)
            {
                incrementToNonZero();
            }

            EIGEN_STRONG_INLINE InnerIterator& operator++()
            {
                EvalIterator::operator++();
                incrementToNonZero();
                return *this;
            }

            using EvalIterator::value;

        protected:
            const XprType& m_view;

        private:
            void incrementToNonZero()
            {
                while ((bool(*this)) && internal::isMuchSmallerThan(value(), m_view.reference(), m_view.epsilon())) { EvalIterator::operator++(); }
            }
        };

        enum
        {
            CoeffReadCost = evaluator<ArgType>::CoeffReadCost,
            Flags = XprType::Flags
        };

        explicit unary_evaluator(const XprType& xpr) : m_argImpl(xpr.nestedExpression()), m_view(xpr) {}

    protected:
        evaluator<ArgType> m_argImpl;
        const XprType& m_view;
    };

    template <typename ArgType> struct unary_evaluator<SparseView<ArgType>, IndexBased> : public evaluator_base<SparseView<ArgType>>
    {
    public:
        typedef SparseView<ArgType> XprType;

    protected:
        enum
        {
            IsRowMajor = (XprType::Flags & RowMajorBit) == RowMajorBit
        };
        typedef typename XprType::Scalar Scalar;
        typedef typename XprType::StorageIndex StorageIndex;

    public:
        class InnerIterator
        {
        public:
            EIGEN_STRONG_INLINE InnerIterator(const unary_evaluator& sve, Index outer) : m_sve(sve), m_inner(0), m_outer(outer), m_end(sve.m_view.innerSize())
            {
                incrementToNonZero();
            }

            EIGEN_STRONG_INLINE InnerIterator& operator++()
            {
                m_inner++;
                incrementToNonZero();
                return *this;
            }

            EIGEN_STRONG_INLINE Scalar value() const
            {
                return (IsRowMajor) ? m_sve.m_argImpl.coeff(m_outer, m_inner) : m_sve.m_argImpl.coeff(m_inner, m_outer);
            }

            EIGEN_STRONG_INLINE StorageIndex index() const { return m_inner; }
            inline Index row() const { return IsRowMajor ? m_outer : index(); }
            inline Index col() const { return IsRowMajor ? index() : m_outer; }

            EIGEN_STRONG_INLINE operator bool() const { return m_inner < m_end && m_inner >= 0; }

        protected:
            const unary_evaluator& m_sve;
            Index m_inner;
            const Index m_outer;
            const Index m_end;

        private:
            void incrementToNonZero()
            {
                while ((bool(*this)) && internal::isMuchSmallerThan(value(), m_sve.m_view.reference(), m_sve.m_view.epsilon())) { m_inner++; }
            }
        };

        enum
        {
            CoeffReadCost = evaluator<ArgType>::CoeffReadCost,
            Flags = XprType::Flags
        };

        explicit unary_evaluator(const XprType& xpr) : m_argImpl(xpr.nestedExpression()), m_view(xpr) {}

    protected:
        evaluator<ArgType> m_argImpl;
        const XprType& m_view;
    };

}  // end namespace internal

/** \ingroup SparseCore_Module
  *
  * \returns a sparse expression of the dense expression \c *this with values smaller than
  * \a reference * \a epsilon removed.
  *
  * This method is typically used when prototyping to convert a quickly assembled dense Matrix \c D to a SparseMatrix \c S:
  * \code
  * MatrixXd D(n,m);
  * SparseMatrix<double> S;
  * S = D.sparseView();             // suppress numerical zeros (exact)
  * S = D.sparseView(reference);
  * S = D.sparseView(reference,epsilon);
  * \endcode
  * where \a reference is a meaningful non zero reference value,
  * and \a epsilon is a tolerance factor defaulting to NumTraits<Scalar>::dummy_precision().
  *
  * \sa SparseMatrixBase::pruned(), class SparseView */
template <typename Derived>
const SparseView<Derived> MatrixBase<Derived>::sparseView(const Scalar& reference, const typename NumTraits<Scalar>::Real& epsilon) const
{
    return SparseView<Derived>(derived(), reference, epsilon);
}

/** \returns an expression of \c *this with values smaller than
  * \a reference * \a epsilon removed.
  *
  * This method is typically used in conjunction with the product of two sparse matrices
  * to automatically prune the smallest values as follows:
  * \code
  * C = (A*B).pruned();             // suppress numerical zeros (exact)
  * C = (A*B).pruned(ref);
  * C = (A*B).pruned(ref,epsilon);
  * \endcode
  * where \c ref is a meaningful non zero reference value.
  * */
template <typename Derived> const SparseView<Derived> SparseMatrixBase<Derived>::pruned(const Scalar& reference, const RealScalar& epsilon) const
{
    return SparseView<Derived>(derived(), reference, epsilon);
}

}  // end namespace Eigen

#endif
